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Ship classification and identification method and system based on track features and deep neural network MobileNet migration training

A technology of deep neural network and classification recognition, which is applied in the field of ship classification recognition methods and systems, can solve problems such as the simultaneous importance of recognition speed and time delay, achieve the advantages of accuracy and average recognition speed, and improve the efficiency of the method Effect

Pending Publication Date: 2022-01-11
PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
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Problems solved by technology

Accurate recognition and real-time monitoring of ship targets requires both accuracy and recognition speed. However, the above research mainly focuses on improving the accuracy of ship target recognition unilaterally, without considering the simultaneous importance of recognition speed and time delay in ship target recognition. sex

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  • Ship classification and identification method and system based on track features and deep neural network MobileNet migration training
  • Ship classification and identification method and system based on track features and deep neural network MobileNet migration training
  • Ship classification and identification method and system based on track features and deep neural network MobileNet migration training

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Embodiment Construction

[0096] The present invention will be further explained below in conjunction with accompanying drawing and specific embodiment:

[0097] Such as figure 1 As shown, a ship classification and recognition method based on track features and deep neural network MobileNet migration training, including:

[0098] Step 1: Carry out data preprocessing for the track data of marked ship types, including deleting the entire abnormal track data and sampling the filtered track data at equal intervals; to ensure the quality of data conversion and reduce data noise for model training interference, improve the accuracy of model recognition;

[0099] Step 2: Mining and extracting the speed, course and acceleration rate of the ship target track point in the track data as the state attribute vector, respectively mapped to the three components of R, G, and B in the RGB color space;

[0100] Step 3: Extract the longitude and latitude of the moving target as the position attribute and project it to ...

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Abstract

The invention discloses a ship classification and identification method and system based on track features and deep neural network MobileNet migration training. The method comprises the following steps of: firstly, mapping characteristics such as speed, course and acceleration obtained by mining track data to an RGB (Red, Green, Blue) color space, and converting the characteristics into track characteristic image data; then, migrating pre-training weights of a depth neural network MobileNet and an Image Net of the depth neural network MobileNet, and training the network by using track feature image data generated before; and finally obtaining a ship type identification model to realize ship classification and identification. The method has obvious advantages in recognition accuracy and speed, and can be effectively applied to classification and recognition of ship targets.

Description

technical field [0001] The invention belongs to the technical field of target recognition, and in particular relates to a ship classification recognition method and system based on track features and deep neural network MobileNet migration training. Background technique [0002] In the era of big data, we can use a large amount of track data to study the laws of maritime traffic and ship behavior patterns in depth, and provide powerful information guarantee for maritime supervision, identification of abnormal behavior and construction of port facilities. However, accurate identification of ship targets is a prerequisite for real-time monitoring and even further research. Especially in special sea areas with intertwined routes and complex sea conditions, targeted intervention measures can be taken to ensure maritime traffic safety by timely identifying unknown ship target types. In addition, precision-guided weapons, unmanned surface ships and integrated maritime reconnaissa...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V20/54G06V10/56G06V10/774G06V10/764G06N3/04G06N3/08
CPCG06N3/04G06N3/08G06N3/084G06F18/214G06F18/24
Inventor 张静李磊王哲可珂莫有权王晓梅周明康
Owner PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
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